Gamma delta (γδ) T cells are essential to protective immunity. In humans, most γδ T cells express Vγ9Vδ2+ T cell receptors (TCRs) that respond to phosphoantigens (pAgs) produced by cellular pathogens and overexpressed by cancers. However, the molecular targets recognized by these γδTCRs are unknown. Here, we identify butyrophilin 2A1 (BTN2A1) as a key ligand that binds to the Vγ9+ TCR γ chain. BTN2A1 associates with another butyrophilin, BTN3A1, and these act together to initiate responses to pAg. Furthermore, binding of a second ligand, possibly BTN3A1, to a separate TCR domain incorporating Vδ2 is also required. This distinctive mode of Ag-dependent T cell activation advances our understanding of diseases involving pAg recognition and creates opportunities for the development of γδ T cell–based immunotherapies.

Proteome analysis is now emerging as key technology for deciphering biological processes and the discovery of biomarkers for diseases from tissues and body fluids. The complexity and wide dynamic range of protein expression poses a formidable challenge to both peptide separation technologies and mass spectrometry (MS). Here we review the efforts that have been undertaken to date, focussing on capillary electrophoresis coupled to mass spectrometry (CE-MS). We discuss CE-MS from an application point of view evaluating its merits and vices in regard to biomarker discovery and clinical applications. As examples, we present the use of CE-MS for the determination of protein patterns in urine, serum, and other body fluids. Finally, the benefits and limitations of CE-MS for the analysis of proteins in clinical samples are discussed against the background of alternative technologies.

CE-MS is a successful proteomic platform for the definition of biomarkers in different body fluids. Besides the biomarker defining experimental parameters, CE migration time and molecular weight, especially biomarker's sequence identity is an indispensable cornerstone for deeper insights into the pathophysiological pathways of diseases or for made-to-measure therapeutic drug design. Therefore, this report presents a detailed discussion of different peptide sequencing platforms consisting of high performance separation method either coupled on-line or off-line to different MS/MS devices, such as MALDI-TOF-TOF, ESI-IT, ESI-QTOF and Fourier transform ion cyclotron resonance, for sequencing indicative peptides. This comparison demonstrates the unique feature of CE-MS technology to serve as a reliable basis for the assignment of peptide sequence data obtained using different separation MS/MS methods to the biomarker defining parameters, CE migration time and molecular weight. Discovery of potential biomarkers by CE-MS enables sequence analysis via MS/MS with platform-independent sample separation. This is due to the fact that the number of basic and neutral polar amino acids of biomarkers sequences distinctly correlates with their CE-MS migration time/molecular weight coordinates. This uniqueness facilitates the independent entry of different sequencing platforms for peptide sequencing of CE-MS-defined biomarkers from highly complex mixtures.

An efficient method was developed for toxicological drug screening in urine by liquid chromatography coupled with electrospray ionization time-of-flight mass spectrometry. The method relies on a large target database of exact monoisotopic masses representing the elemental formulae of reference drugs and their metabolites. Mass spectral identification is based on matching measured accurate mass and isotopic pattern (SigmaFit) of a sample component with those in the database. Data post-processing software was developed for automated reporting of findings in an easily interpretable form. The mean and median of SigmaFit for true-positive findings were 0.0066 and 0.0051, respectively. The mean and median of mass error absolute values for true-positive findings were 2.51 and 2.17 ppm, respectively, corresponding to 0.65 and 0.60 mTh. For routine screening practice, a SigmaFit tolerance of 0.03 and a mass tolerance of 10 ppm were chosen. Ion abundance differences from urine extracts did not affect the accuracy of the automatically acquired SigmaFit or mass values. The results show that isotopic pattern matching by SigmaFit is a powerful means of identification in addition to accurate mass measurement.